Traditional emotion detection technologies enable organizations to analyze recorded calls for heightened states of emotion to cost-effectively improve customer satisfaction and agent effectiveness. Emotion detection is part of the broader speech analytics market, now the fastest growing segment within the contact center technology market, according to advisory firm DMG Consulting (www.dmgconsult.com).

While compliance and regulatory mandates continue to fuel interest in the broader speech analytics market, the potential uses for emotion detection remain largely untapped. With its ability to help organizations reduce costs and improve customer service, why is this the case?

Based on the current vendor landscape, third-party industry analysis, and end-user feedback, four primary issues appear to be at the root of this perplexing trend.

Lack of Real-Time FeaturesThe vast majority of emotion detection products today are designed to analyze calls after they take place. This eliminates the opportunity to proactively intervene during problematic calls. It also means that information about the call is often irrelevant by the time a problem is detected, and some information will inevitably "fall through the cracks" altogether. To make the most of emotion detection, products must be able to identify the emotional state of a customer as it is occurring, and include real-time supervision and alerts so organizations can achieve the ultimate objective of first-call resolution.

Lack of Agent Versus Caller AnalysisMany emotion detection products don't enable organizations to distinguish between customer and agent emotion, which makes it impossible to access and sort results by agent for improved training and quality control. This includes the need to ensure agents adhere to scripts, particularly critical as compliance and regulatory requirements become more stringent. It also enables supervisors to set alerts differently for agents and customers - such as alerts that might be set at a lower anger threshold for agents than for customers. Finally, organizations can use this capability to develop teams of agents trained to handle highly emotional calls. These teams can be set up as "virtual" agents and calls can be automatically routed via automatic call distribution based on this skill-set for assessment and resolution.

Lack of Emotion Distinction & Organizational FeedbackMany emotion detection products don't distinguish between type of heightened emotion, such as the distinction between happiness and anger. Emotion detection products should include this analysis so organizations can identify which behaviors are contributing to positive or negative customer and agent emotion. Organizations can also use this information to identify strengths and areas for improvement in sales, marketing and operations. This capability can even be used to identify and highlight customer testimonials and to tie into other customer feedback programs.

Overly Complex and PriceyMost emotion detection products are pricey and require third-party hardware components. In addition, these standalone offerings must be integrated with existing communications systems. The result is costly and complex system installation and management. With the trend toward contact center convergence, emotion detection products can now be offered as part of a single-platform software suite. By consolidating functions on a single platform, organizations can reduce costs, simplify management, and maximize functionality.

In a tough economy reducing costs and retaining customers are paramount. Emotion detection has the potential to address these issues head-on, but only when products begin addressing the remaining customer requirements for key functionality, simplicity and affordability.

About the authorJoseph A. Staples is senior vice president of worldwide marketing for Interactive Intelligence. He oversees the global marketing efforts of the company's contact center and IP communication product lines, and brings more than 25 years of experience in technology and marketing.

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